Optimising the Software Development Process with Artificial Intelligence

Optimising the Software Development Process with Artificial Intelligence
Author: José Raúl Romero
Publisher: Springer Nature
Total Pages: 349
Release: 2023-07-19
Genre: Computers
ISBN: 9811999481

This book offers a practical introduction to the use of artificial intelligence (AI) techniques to improve and optimise the various phases of the software development process, from the initial project planning to the latest deployment. All chapters were written by leading experts in the field and include practical and reproducible examples. Following the introductory chapter, Chapters 2-9 respectively apply AI techniques to the classic phases of the software development process: project management, requirement engineering, analysis and design, coding, cloud deployment, unit and system testing, and maintenance. Subsequently, Chapters 10 and 11 provide foundational tutorials on the AI techniques used in the preceding chapters: metaheuristics and machine learning. Given its scope and focus, the book represents a valuable resource for researchers, practitioners and students with a basic grasp of software engineering.

Artificial Intelligence Methods for Optimization of the Software Testing Process

Artificial Intelligence Methods for Optimization of the Software Testing Process
Author: Sahar Tahvili
Publisher: Academic Press
Total Pages: 232
Release: 2022-07-21
Genre: Computers
ISBN: 0323912826

Artificial Intelligence Methods for Optimization of the Software Testing Process: With Practical Examples and Exercises presents different AI-based solutions for overcoming the uncertainty found in many initial testing problems. The concept of intelligent decision making is presented as a multi-criteria, multi-objective undertaking. The book provides guidelines on how to manage diverse types of uncertainty with intelligent decision-making that can help subject matter experts in many industries improve various processes in a more efficient way. As the number of required test cases for testing a product can be large (in industry more than 10,000 test cases are usually created). Executing all these test cases without any particular order can impact the results of the test execution, hence this book fills the need for a comprehensive resource on the topics on the how's, what's and whys. To learn more about Elsevier's Series, Uncertainty, Computational Techniques and Decision Intelligence, please visit this link: https://www.elsevier.com/books-and-journals/book-series/uncertainty-computational-techniques-and-decision-intelligence - Presents one of the first empirical studies in the field, contrasting theoretical assumptions on innovations in a real industrial environment with a large set of use cases from developed and developing testing processes at various large industries - Explores specific comparative methodologies, focusing on developed and developing AI-based solutions - Serves as a guideline for conducting industrial research in the artificial intelligence and software testing domain - Explains all proposed solutions through real industrial case studies

Applications of Artificial Intelligence in Process Systems Engineering

Applications of Artificial Intelligence in Process Systems Engineering
Author: Jingzheng Ren
Publisher: Elsevier
Total Pages: 542
Release: 2021-06-05
Genre: Technology & Engineering
ISBN: 012821743X

Applications of Artificial Intelligence in Process Systems Engineering offers a broad perspective on the issues related to artificial intelligence technologies and their applications in chemical and process engineering. The book comprehensively introduces the methodology and applications of AI technologies in process systems engineering, making it an indispensable reference for researchers and students. As chemical processes and systems are usually non-linear and complex, thus making it challenging to apply AI methods and technologies, this book is an ideal resource on emerging areas such as cloud computing, big data, the industrial Internet of Things and deep learning. With process systems engineering's potential to become one of the driving forces for the development of AI technologies, this book covers all the right bases. - Explains the concept of machine learning, deep learning and state-of-the-art intelligent algorithms - Discusses AI-based applications in process modeling and simulation, process integration and optimization, process control, and fault detection and diagnosis - Gives direction to future development trends of AI technologies in chemical and process engineering

Handbook of Research on Manufacturing Process Modeling and Optimization Strategies

Handbook of Research on Manufacturing Process Modeling and Optimization Strategies
Author: Das, Raja
Publisher: IGI Global
Total Pages: 556
Release: 2017-03-10
Genre: Business & Economics
ISBN: 152252441X

Recent improvements in business process strategies have allowed more opportunities to attain greater developmental performances. This has led to higher success in day-to-day production and overall competitive advantage. The Handbook of Research on Manufacturing Process Modeling and Optimization Strategies is a pivotal reference source for the latest research on the various manufacturing methodologies and highlights the best optimization approaches to achieve boosted process performance. Featuring extensive coverage on relevant areas such as genetic algorithms, fuzzy set theory, and soft computing techniques, this publication is an ideal resource for researchers, practitioners, academicians, designers, manufacturing engineers, and institutions involved in design and manufacturing projects.

Evolutionary Computation and Optimization Algorithms in Software Engineering: Applications and Techniques

Evolutionary Computation and Optimization Algorithms in Software Engineering: Applications and Techniques
Author: Chis, Monica
Publisher: IGI Global
Total Pages: 282
Release: 2010-06-30
Genre: Education
ISBN: 1615208100

Evolutionary Computation and Optimization Algorithms in Software Engineering: Applications and Techniques lays the foundation for the successful integration of evolutionary computation into software engineering. It surveys techniques ranging from genetic algorithms, to swarm optimization theory, to ant colony optimization, demonstrating their uses and capabilities. These techniques are applied to aspects of software engineering such as software testing, quality assessment, reliability assessment, and fault prediction models, among others, to providing researchers, scholars and students with the knowledge needed to expand this burgeoning application.

Artificial Intelligence Methods For Software Engineering

Artificial Intelligence Methods For Software Engineering
Author: Meir Kalech
Publisher: World Scientific
Total Pages: 457
Release: 2021-06-15
Genre: Computers
ISBN: 9811239932

Software is an integral part of our lives today. Modern software systems are highly complex and often pose new challenges in different aspects of Software Engineering (SE).Artificial Intelligence (AI) is a growing field in computer science that has been proven effective in applying and developing AI techniques to address various SE challenges.This unique compendium covers applications of state-of-the-art AI techniques to the key areas of SE (design, development, debugging, testing, etc).All the materials presented are up-to-date. This reference text will benefit researchers, academics, professionals, and postgraduate students in AI, machine learning and software engineering.Related Link(s)

Human vs ChatGPT – Language of Advertising in Beauty Products Advertisements

Human vs ChatGPT – Language of Advertising in Beauty Products Advertisements
Author: Ida Skubis
Publisher: CRC Press
Total Pages: 115
Release: 2024-11-21
Genre: Computers
ISBN: 1040298036

This book systematically investigates the linguistic strategies employed in beauty product advertising to assess their persuasive and manipulative effects. The work is divided into two sections: a review of relevant literature and an empirical analysis of advertisements. The analysis initially focuses on the linguistic features of advertisements created by humans prior to the introduction of ChatGPT, examining the linguistic measures used and their methods of persuasion and manipulation. Subsequent sections provide a detailed examination of advertisements generated by ChatGPT versions 3.5 and 4.0, analysing the artificial intelligence’s use of linguistic techniques. This includes a meta-analysis where ChatGPT itself discusses the linguistic strategies it employs. The ultimate goal is to compare and contrast the effectiveness and linguistic devices used in advertisements crafted by humans and those by ChatGPT, analysing how AI influences the language of advertising and its impact on consumer behaviour.

Advancing Software Engineering Through AI, Federated Learning, and Large Language Models

Advancing Software Engineering Through AI, Federated Learning, and Large Language Models
Author: Sharma, Avinash Kumar
Publisher: IGI Global
Total Pages: 375
Release: 2024-05-02
Genre: Computers
ISBN:

The rapid evolution of software engineering demands innovative approaches to meet the growing complexity and scale of modern software systems. Traditional methods often need help to keep pace with the demands for efficiency, reliability, and scalability. Manual development, testing, and maintenance processes are time-consuming and error-prone, leading to delays and increased costs. Additionally, integrating new technologies, such as AI, ML, Federated Learning, and Large Language Models (LLM), presents unique challenges in terms of implementation and ethical considerations. Advancing Software Engineering Through AI, Federated Learning, and Large Language Models provides a compelling solution by comprehensively exploring how AI, ML, Federated Learning, and LLM intersect with software engineering. By presenting real-world case studies, practical examples, and implementation guidelines, the book ensures that readers can readily apply these concepts in their software engineering projects. Researchers, academicians, practitioners, industrialists, and students will benefit from the interdisciplinary insights provided by experts in AI, ML, software engineering, and ethics.